testBowler.r
Vishal
Thu Mar 07 19:45:46 2019
testbowling2007 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2007testbowlingrating.csv")
testbowling2008 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2008testbowlingrating.csv")
testbowling2009 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2009testbowlingrating.csv")
testbowling2010 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2010testbowlingrating.csv")
testbowling2011 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2011testbowlingrating.csv")
testbowling2012 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2012testbowlingrating.csv")
testbowling2013 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2013testbowlingrating.csv")
testbowling2014 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2014testbowlingrating.csv")
testbowling2015 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2015testbowlingrating.csv")
testbowling2016 <- read.csv("D:\\Vishal\\III year\\Data Analytics\\Assignment II\\Player Ratings\\2016testbowlingrating.csv")
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, uniondataTestBowling <- bind_rows(testbowling2007, testbowling2008, testbowling2009, testbowling2010, testbowling2011,
testbowling2012, testbowling2013, testbowling2014, testbowling2015, testbowling2016)## Warning in bind_rows_(x, .id): Unequal factor levels: coercing to character## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vector
## Warning in bind_rows_(x, .id): binding character and factor vector,
## coercing into character vectorsummary(dataTestBowling)## Name Rating LogRating
## Length:1000 Min. : 7.0 Min. :0.8451
## Class :character 1st Qu.:128.8 1st Qu.:2.1098
## Mode :character Median :293.0 Median :2.4669
## Mean :332.2 Mean :2.3630
## 3rd Qu.:514.0 3rd Qu.:2.7110
## Max. :916.0 Max. :2.9619library(ggplot2)
dataTestBowling <- dataTestBowling %>%
group_by(Name) %>%
summarise(avg = mean(Rating))
set.seed(20)
ballcluster <- kmeans(dataTestBowling[, 2], 5)
ballcluster$cluster <- as.factor(ballcluster$cluster)
ggplot(dataTestBowling, aes(dataTestBowling$Name, avg, color = ballcluster$cluster)) +
geom_point(size = 2) +
scale_color_manual(labels = c("Good", "Best", "Useless", "Better", "Average"), values = c("blue", "red", "green", "cyan", "black")) +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) +
ggtitle("Test Bowling Ratings(2007-2016)")
dat <- arrange(dataTestBowling, desc(avg)) %>%
mutate(rank = 1:nrow(dataTestBowling))
dataTestBowling <- merge(dataTestBowling, dat, by = "Name")
library(plotly)##
## Attaching package: 'plotly'## The following object is masked from 'package:ggplot2':
##
## last_plot## The following object is masked from 'package:stats':
##
## filter## The following object is masked from 'package:graphics':
##
## layoutp <- plot_ly(dataTestBowling, x = ~Name, y = ~avg.x, type = 'scatter',
mode = 'markers', color = ballcluster$cluster,
text = ~paste('Rank: ', rank))
pdat <- dataTestBowling[, -1]
norm <- function(x) {((x - min(x))/ (max(x) - min(x)))}
dat_norm <- as.data.frame(lapply(dat, norm))
dat_norm## avg.x avg.y rank
## 1 0.081463991 0.081463991 0.835249042
## 2 0.182998819 0.182998819 0.632183908
## 3 0.360094451 0.360094451 0.402298851
## 4 0.440377804 0.440377804 0.295019157
## 5 0.142351155 0.142351155 0.704980843
## 6 0.730421094 0.730421094 0.084291188
## 7 0.192443920 0.192443920 0.624521073
## 8 0.011806375 0.011806375 0.957854406
## 9 0.082880756 0.082880756 0.827586207
## 10 0.839433294 0.839433294 0.034482759
## 11 0.376623377 0.376623377 0.379310345
## 12 0.106257379 0.106257379 0.770114943
## 13 0.000000000 0.000000000 0.992337165
## 14 0.662337662 0.662337662 0.145593870
## 15 0.263282172 0.263282172 0.528735632
## 16 0.096812279 0.096812279 0.789272031
## 17 0.170306966 0.170306966 0.655172414
## 18 0.543936583 0.543936583 0.237547893
## 19 0.085005903 0.085005903 0.823754789
## 20 0.397874852 0.397874852 0.348659004
## 21 0.030696576 0.030696576 0.919540230
## 22 0.010625738 0.010625738 0.961685824
## 23 0.028335301 0.028335301 0.934865900
## 24 0.423455333 0.423455333 0.314176245
## 25 0.544470681 0.544470681 0.229885057
## 26 0.005903188 0.005903188 0.980842912
## 27 0.055489965 0.055489965 0.873563218
## 28 0.160566706 0.160566706 0.670498084
## 29 0.287780401 0.287780401 0.501915709
## 30 0.839433294 0.839433294 0.038314176
## 31 0.211334120 0.211334120 0.601532567
## 32 0.079693034 0.079693034 0.842911877
## 33 0.548110980 0.548110980 0.226053640
## 34 0.094451004 0.094451004 0.804597701
## 35 0.378984652 0.378984652 0.371647510
## 36 0.077922078 0.077922078 0.846743295
## 37 0.252262889 0.252262889 0.551724138
## 38 0.234159780 0.234159780 0.570881226
## 39 0.534041716 0.534041716 0.245210728
## 40 0.173553719 0.173553719 0.643678161
## 41 0.688508461 0.688508461 0.114942529
## 42 0.473238882 0.473238882 0.279693487
## 43 0.487839433 0.487839433 0.275862069
## 44 0.041794569 0.041794569 0.896551724
## 45 0.440968123 0.440968123 0.291187739
## 46 0.393152302 0.393152302 0.356321839
## 47 0.717827627 0.717827627 0.099616858
## 48 0.097992916 0.097992916 0.781609195
## 49 0.436161241 0.436161241 0.298850575
## 50 0.537190083 0.537190083 0.241379310
## 51 0.338252656 0.338252656 0.429118774
## 52 0.677538371 0.677538371 0.130268199
## 53 0.035925114 0.035925114 0.908045977
## 54 0.526564345 0.526564345 0.249042146
## 55 0.982880756 0.982880756 0.003831418
## 56 0.719303424 0.719303424 0.095785441
## 57 0.126918536 0.126918536 0.735632184
## 58 0.080578512 0.080578512 0.839080460
## 59 0.363636364 0.363636364 0.394636015
## 60 0.314639906 0.314639906 0.463601533
## 61 0.593663912 0.593663912 0.183908046
## 62 0.106257379 0.106257379 0.773946360
## 63 0.058441558 0.058441558 0.869731801
## 64 0.212514758 0.212514758 0.593869732
## 65 0.396694215 0.396694215 0.352490421
## 66 0.849350649 0.849350649 0.026819923
## 67 0.654309327 0.654309327 0.149425287
## 68 0.146694215 0.146694215 0.693486590
## 69 0.664580874 0.664580874 0.141762452
## 70 0.322707595 0.322707595 0.459770115
## 71 0.043683589 0.043683589 0.885057471
## 72 0.720188902 0.720188902 0.091954023
## 73 0.253837072 0.253837072 0.540229885
## 74 0.612750885 0.612750885 0.176245211
## 75 0.017709563 0.017709563 0.950191571
## 76 0.342384888 0.342384888 0.413793103
## 77 0.334356553 0.334356553 0.440613027
## 78 0.020661157 0.020661157 0.942528736
## 79 0.203069658 0.203069658 0.616858238
## 80 0.010625738 0.010625738 0.965517241
## 81 0.133412043 0.133412043 0.716475096
## 82 0.171529769 0.171529769 0.651340996
## 83 0.493900039 0.493900039 0.268199234
## 84 0.062180244 0.062180244 0.862068966
## 85 0.207005116 0.207005116 0.605363985
## 86 0.557654467 0.557654467 0.218390805
## 87 0.093270366 0.093270366 0.808429119
## 88 0.585123967 0.585123967 0.195402299
## 89 0.625737898 0.625737898 0.168582375
## 90 0.602833530 0.602833530 0.180076628
## 91 0.814403778 0.814403778 0.045977011
## 92 0.327922078 0.327922078 0.448275862
## 93 0.271546635 0.271546635 0.509578544
## 94 0.243063754 0.243063754 0.563218391
## 95 0.726682409 0.726682409 0.088122605
## 96 0.313852814 0.313852814 0.471264368
## 97 0.339433294 0.339433294 0.421455939
## 98 0.566706021 0.566706021 0.206896552
## 99 0.684938438 0.684938438 0.118773946
## 100 0.086776860 0.086776860 0.816091954
## 101 0.003541913 0.003541913 0.984674330
## 102 0.423848878 0.423848878 0.310344828
## 103 0.374852420 0.374852420 0.383141762
## 104 0.245235284 0.245235284 0.559386973
## 105 0.271546635 0.271546635 0.513409962
## 106 0.046044864 0.046044864 0.881226054
## 107 0.544273908 0.544273908 0.233716475
## 108 0.232349469 0.232349469 0.574712644
## 109 0.325708383 0.325708383 0.452107280
## 110 0.226977568 0.226977568 0.582375479
## 111 0.009838646 0.009838646 0.973180077
## 112 0.059031877 0.059031877 0.865900383
## 113 0.503187721 0.503187721 0.260536398
## 114 0.345336482 0.345336482 0.409961686
## 115 0.388823298 0.388823298 0.360153257
## 116 0.497441952 0.497441952 0.264367816
## 117 0.121605667 0.121605667 0.743295019
## 118 0.129870130 0.129870130 0.724137931
## 119 0.177390791 0.177390791 0.636015326
## 120 0.803128689 0.803128689 0.049808429
## 121 0.136429227 0.136429227 0.712643678
## 122 0.041659639 0.041659639 0.900383142
## 123 0.203659976 0.203659976 0.613026820
## 124 0.841794569 0.841794569 0.030651341
## 125 0.067296340 0.067296340 0.858237548
## 126 0.141676505 0.141676505 0.708812261
## 127 0.000000000 0.000000000 0.996168582
## 128 0.342384888 0.342384888 0.417624521
## 129 0.679929162 0.679929162 0.126436782
## 130 1.000000000 1.000000000 0.000000000
## 131 0.128807556 0.128807556 0.731800766
## 132 0.924832743 0.924832743 0.015325670
## 133 0.035419126 0.035419126 0.911877395
## 134 0.250885478 0.250885478 0.555555556
## 135 0.189492326 0.189492326 0.628352490
## 136 0.634171024 0.634171024 0.153256705
## 137 0.291223928 0.291223928 0.494252874
## 138 0.304604486 0.304604486 0.482758621
## 139 0.301062574 0.301062574 0.490421456
## 140 0.489571035 0.489571035 0.272030651
## 141 0.076741440 0.076741440 0.854406130
## 142 0.358126722 0.358126722 0.406130268
## 143 0.314049587 0.314049587 0.467432950
## 144 0.128886265 0.128886265 0.727969349
## 145 0.785419126 0.785419126 0.061302682
## 146 0.264593992 0.264593992 0.524904215
## 147 0.590318772 0.590318772 0.191570881
## 148 0.382526564 0.382526564 0.367816092
## 149 0.111570248 0.111570248 0.766283525
## 150 0.508067690 0.508067690 0.256704981
## 151 0.240850059 0.240850059 0.567049808
## 152 0.000000000 0.000000000 1.000000000
## 153 0.172373081 0.172373081 0.647509579
## 154 0.176623377 0.176623377 0.639846743
## 155 0.086186541 0.086186541 0.819923372
## 156 0.253837072 0.253837072 0.544061303
## 157 0.676033058 0.676033058 0.134099617
## 158 0.289649744 0.289649744 0.498084291
## 159 0.577036600 0.577036600 0.203065134
## 160 0.142463597 0.142463597 0.701149425
## 161 0.018890201 0.018890201 0.946360153
## 162 0.043290043 0.043290043 0.888888889
## 163 0.142857143 0.142857143 0.697318008
## 164 0.212514758 0.212514758 0.597701149
## 165 0.263282172 0.263282172 0.532567050
## 166 0.560507674 0.560507674 0.214559387
## 167 0.752656434 0.752656434 0.072796935
## 168 0.055489965 0.055489965 0.877394636
## 169 0.583530106 0.583530106 0.199233716
## 170 0.116883117 0.116883117 0.758620690
## 171 0.275088548 0.275088548 0.505747126
## 172 0.671192444 0.671192444 0.137931034
## 173 0.303227076 0.303227076 0.486590038
## 174 0.794096812 0.794096812 0.053639847
## 175 0.014757969 0.014757969 0.954022989
## 176 0.632113341 0.632113341 0.160919540
## 177 0.170011806 0.170011806 0.659003831
## 178 0.689885872 0.689885872 0.111111111
## 179 0.400236128 0.400236128 0.340996169
## 180 0.077922078 0.077922078 0.850574713
## 181 0.405903188 0.405903188 0.337164751
## 182 0.123730815 0.123730815 0.739463602
## 183 0.367768595 0.367768595 0.390804598
## 184 0.030696576 0.030696576 0.923371648
## 185 0.564738292 0.564738292 0.210727969
## 186 0.324970484 0.324970484 0.455938697
## 187 0.034238489 0.034238489 0.915708812
## 188 0.328807556 0.328807556 0.444444444
## 189 0.152499016 0.152499016 0.685823755
## 190 0.226682409 0.226682409 0.586206897
## 191 0.690672963 0.690672963 0.107279693
## 192 0.118654073 0.118654073 0.754789272
## 193 0.736586646 0.736586646 0.076628352
## 194 0.043093270 0.043093270 0.892720307
## 195 0.777646596 0.777646596 0.065134100
## 196 0.467532468 0.467532468 0.283524904
## 197 0.621802440 0.621802440 0.172413793
## 198 0.198937426 0.198937426 0.620689655
## 199 0.552538371 0.552538371 0.222222222
## 200 0.133116883 0.133116883 0.720306513
## 201 0.852420307 0.852420307 0.022988506
## 202 0.113341204 0.113341204 0.762452107
## 203 0.149547422 0.149547422 0.689655172
## 204 0.220779221 0.220779221 0.590038314
## 205 0.912632822 0.912632822 0.019157088
## 206 0.312278630 0.312278630 0.478927203
## 207 0.040436836 0.040436836 0.904214559
## 208 0.161072694 0.161072694 0.666666667
## 209 0.415289256 0.415289256 0.329501916
## 210 0.377213695 0.377213695 0.375478927
## 211 0.009445100 0.009445100 0.977011494
## 212 0.416765053 0.416765053 0.325670498
## 213 0.591263282 0.591263282 0.187739464
## 214 0.628605161 0.628605161 0.164750958
## 215 0.313105077 0.313105077 0.475095785
## 216 0.467532468 0.467532468 0.287356322
## 217 0.029515939 0.029515939 0.931034483
## 218 0.096221960 0.096221960 0.793103448
## 219 0.339433294 0.339433294 0.425287356
## 220 0.097992916 0.097992916 0.785440613
## 221 0.736245573 0.736245573 0.080459770
## 222 0.030303030 0.030303030 0.927203065
## 223 0.102715466 0.102715466 0.777777778
## 224 0.384651712 0.384651712 0.363984674
## 225 0.360881543 0.360881543 0.398467433
## 226 0.632428178 0.632428178 0.157088123
## 227 0.814639906 0.814639906 0.042145594
## 228 0.121343303 0.121343303 0.750957854
## 229 0.158795750 0.158795750 0.674329502
## 230 0.407319953 0.407319953 0.333333333
## 231 0.001180638 0.001180638 0.988505747
## 232 0.154663518 0.154663518 0.678160920
## 233 0.702951594 0.702951594 0.103448276
## 234 0.373081464 0.373081464 0.386973180
## 235 0.520923521 0.520923521 0.252873563
## 236 0.265938607 0.265938607 0.521072797
## 237 0.229634002 0.229634002 0.578544061
## 238 0.165092483 0.165092483 0.662835249
## 239 0.204840614 0.204840614 0.609195402
## 240 0.429752066 0.429752066 0.306513410
## 241 0.095238095 0.095238095 0.800766284
## 242 0.010625738 0.010625738 0.969348659
## 243 0.433293979 0.433293979 0.302681992
## 244 0.423258560 0.423258560 0.318007663
## 245 0.421015348 0.421015348 0.321839080
## 246 0.336650363 0.336650363 0.432950192
## 247 0.680243998 0.680243998 0.122605364
## 248 0.938842975 0.938842975 0.007662835
## 249 0.252951594 0.252951594 0.547892720
## 250 0.121605667 0.121605667 0.747126437
## 251 0.262691854 0.262691854 0.536398467
## 252 0.096221960 0.096221960 0.796934866
## 253 0.793388430 0.793388430 0.057471264
## 254 0.154663518 0.154663518 0.681992337
## 255 0.335694608 0.335694608 0.436781609
## 256 0.027154664 0.027154664 0.938697318
## 257 0.270365998 0.270365998 0.517241379
## 258 0.932703660 0.932703660 0.011494253
## 259 0.082644628 0.082644628 0.831417625
## 260 0.090200708 0.090200708 0.812260536
## 261 0.768763704 0.768763704 0.068965517
## 262 0.399449036 0.399449036 0.344827586dat_train <- dat[1:183, ]
dat_test <- dat[184:262, ]
dat_norm## avg.x avg.y rank
## 1 0.081463991 0.081463991 0.835249042
## 2 0.182998819 0.182998819 0.632183908
## 3 0.360094451 0.360094451 0.402298851
## 4 0.440377804 0.440377804 0.295019157
## 5 0.142351155 0.142351155 0.704980843
## 6 0.730421094 0.730421094 0.084291188
## 7 0.192443920 0.192443920 0.624521073
## 8 0.011806375 0.011806375 0.957854406
## 9 0.082880756 0.082880756 0.827586207
## 10 0.839433294 0.839433294 0.034482759
## 11 0.376623377 0.376623377 0.379310345
## 12 0.106257379 0.106257379 0.770114943
## 13 0.000000000 0.000000000 0.992337165
## 14 0.662337662 0.662337662 0.145593870
## 15 0.263282172 0.263282172 0.528735632
## 16 0.096812279 0.096812279 0.789272031
## 17 0.170306966 0.170306966 0.655172414
## 18 0.543936583 0.543936583 0.237547893
## 19 0.085005903 0.085005903 0.823754789
## 20 0.397874852 0.397874852 0.348659004
## 21 0.030696576 0.030696576 0.919540230
## 22 0.010625738 0.010625738 0.961685824
## 23 0.028335301 0.028335301 0.934865900
## 24 0.423455333 0.423455333 0.314176245
## 25 0.544470681 0.544470681 0.229885057
## 26 0.005903188 0.005903188 0.980842912
## 27 0.055489965 0.055489965 0.873563218
## 28 0.160566706 0.160566706 0.670498084
## 29 0.287780401 0.287780401 0.501915709
## 30 0.839433294 0.839433294 0.038314176
## 31 0.211334120 0.211334120 0.601532567
## 32 0.079693034 0.079693034 0.842911877
## 33 0.548110980 0.548110980 0.226053640
## 34 0.094451004 0.094451004 0.804597701
## 35 0.378984652 0.378984652 0.371647510
## 36 0.077922078 0.077922078 0.846743295
## 37 0.252262889 0.252262889 0.551724138
## 38 0.234159780 0.234159780 0.570881226
## 39 0.534041716 0.534041716 0.245210728
## 40 0.173553719 0.173553719 0.643678161
## 41 0.688508461 0.688508461 0.114942529
## 42 0.473238882 0.473238882 0.279693487
## 43 0.487839433 0.487839433 0.275862069
## 44 0.041794569 0.041794569 0.896551724
## 45 0.440968123 0.440968123 0.291187739
## 46 0.393152302 0.393152302 0.356321839
## 47 0.717827627 0.717827627 0.099616858
## 48 0.097992916 0.097992916 0.781609195
## 49 0.436161241 0.436161241 0.298850575
## 50 0.537190083 0.537190083 0.241379310
## 51 0.338252656 0.338252656 0.429118774
## 52 0.677538371 0.677538371 0.130268199
## 53 0.035925114 0.035925114 0.908045977
## 54 0.526564345 0.526564345 0.249042146
## 55 0.982880756 0.982880756 0.003831418
## 56 0.719303424 0.719303424 0.095785441
## 57 0.126918536 0.126918536 0.735632184
## 58 0.080578512 0.080578512 0.839080460
## 59 0.363636364 0.363636364 0.394636015
## 60 0.314639906 0.314639906 0.463601533
## 61 0.593663912 0.593663912 0.183908046
## 62 0.106257379 0.106257379 0.773946360
## 63 0.058441558 0.058441558 0.869731801
## 64 0.212514758 0.212514758 0.593869732
## 65 0.396694215 0.396694215 0.352490421
## 66 0.849350649 0.849350649 0.026819923
## 67 0.654309327 0.654309327 0.149425287
## 68 0.146694215 0.146694215 0.693486590
## 69 0.664580874 0.664580874 0.141762452
## 70 0.322707595 0.322707595 0.459770115
## 71 0.043683589 0.043683589 0.885057471
## 72 0.720188902 0.720188902 0.091954023
## 73 0.253837072 0.253837072 0.540229885
## 74 0.612750885 0.612750885 0.176245211
## 75 0.017709563 0.017709563 0.950191571
## 76 0.342384888 0.342384888 0.413793103
## 77 0.334356553 0.334356553 0.440613027
## 78 0.020661157 0.020661157 0.942528736
## 79 0.203069658 0.203069658 0.616858238
## 80 0.010625738 0.010625738 0.965517241
## 81 0.133412043 0.133412043 0.716475096
## 82 0.171529769 0.171529769 0.651340996
## 83 0.493900039 0.493900039 0.268199234
## 84 0.062180244 0.062180244 0.862068966
## 85 0.207005116 0.207005116 0.605363985
## 86 0.557654467 0.557654467 0.218390805
## 87 0.093270366 0.093270366 0.808429119
## 88 0.585123967 0.585123967 0.195402299
## 89 0.625737898 0.625737898 0.168582375
## 90 0.602833530 0.602833530 0.180076628
## 91 0.814403778 0.814403778 0.045977011
## 92 0.327922078 0.327922078 0.448275862
## 93 0.271546635 0.271546635 0.509578544
## 94 0.243063754 0.243063754 0.563218391
## 95 0.726682409 0.726682409 0.088122605
## 96 0.313852814 0.313852814 0.471264368
## 97 0.339433294 0.339433294 0.421455939
## 98 0.566706021 0.566706021 0.206896552
## 99 0.684938438 0.684938438 0.118773946
## 100 0.086776860 0.086776860 0.816091954
## 101 0.003541913 0.003541913 0.984674330
## 102 0.423848878 0.423848878 0.310344828
## 103 0.374852420 0.374852420 0.383141762
## 104 0.245235284 0.245235284 0.559386973
## 105 0.271546635 0.271546635 0.513409962
## 106 0.046044864 0.046044864 0.881226054
## 107 0.544273908 0.544273908 0.233716475
## 108 0.232349469 0.232349469 0.574712644
## 109 0.325708383 0.325708383 0.452107280
## 110 0.226977568 0.226977568 0.582375479
## 111 0.009838646 0.009838646 0.973180077
## 112 0.059031877 0.059031877 0.865900383
## 113 0.503187721 0.503187721 0.260536398
## 114 0.345336482 0.345336482 0.409961686
## 115 0.388823298 0.388823298 0.360153257
## 116 0.497441952 0.497441952 0.264367816
## 117 0.121605667 0.121605667 0.743295019
## 118 0.129870130 0.129870130 0.724137931
## 119 0.177390791 0.177390791 0.636015326
## 120 0.803128689 0.803128689 0.049808429
## 121 0.136429227 0.136429227 0.712643678
## 122 0.041659639 0.041659639 0.900383142
## 123 0.203659976 0.203659976 0.613026820
## 124 0.841794569 0.841794569 0.030651341
## 125 0.067296340 0.067296340 0.858237548
## 126 0.141676505 0.141676505 0.708812261
## 127 0.000000000 0.000000000 0.996168582
## 128 0.342384888 0.342384888 0.417624521
## 129 0.679929162 0.679929162 0.126436782
## 130 1.000000000 1.000000000 0.000000000
## 131 0.128807556 0.128807556 0.731800766
## 132 0.924832743 0.924832743 0.015325670
## 133 0.035419126 0.035419126 0.911877395
## 134 0.250885478 0.250885478 0.555555556
## 135 0.189492326 0.189492326 0.628352490
## 136 0.634171024 0.634171024 0.153256705
## 137 0.291223928 0.291223928 0.494252874
## 138 0.304604486 0.304604486 0.482758621
## 139 0.301062574 0.301062574 0.490421456
## 140 0.489571035 0.489571035 0.272030651
## 141 0.076741440 0.076741440 0.854406130
## 142 0.358126722 0.358126722 0.406130268
## 143 0.314049587 0.314049587 0.467432950
## 144 0.128886265 0.128886265 0.727969349
## 145 0.785419126 0.785419126 0.061302682
## 146 0.264593992 0.264593992 0.524904215
## 147 0.590318772 0.590318772 0.191570881
## 148 0.382526564 0.382526564 0.367816092
## 149 0.111570248 0.111570248 0.766283525
## 150 0.508067690 0.508067690 0.256704981
## 151 0.240850059 0.240850059 0.567049808
## 152 0.000000000 0.000000000 1.000000000
## 153 0.172373081 0.172373081 0.647509579
## 154 0.176623377 0.176623377 0.639846743
## 155 0.086186541 0.086186541 0.819923372
## 156 0.253837072 0.253837072 0.544061303
## 157 0.676033058 0.676033058 0.134099617
## 158 0.289649744 0.289649744 0.498084291
## 159 0.577036600 0.577036600 0.203065134
## 160 0.142463597 0.142463597 0.701149425
## 161 0.018890201 0.018890201 0.946360153
## 162 0.043290043 0.043290043 0.888888889
## 163 0.142857143 0.142857143 0.697318008
## 164 0.212514758 0.212514758 0.597701149
## 165 0.263282172 0.263282172 0.532567050
## 166 0.560507674 0.560507674 0.214559387
## 167 0.752656434 0.752656434 0.072796935
## 168 0.055489965 0.055489965 0.877394636
## 169 0.583530106 0.583530106 0.199233716
## 170 0.116883117 0.116883117 0.758620690
## 171 0.275088548 0.275088548 0.505747126
## 172 0.671192444 0.671192444 0.137931034
## 173 0.303227076 0.303227076 0.486590038
## 174 0.794096812 0.794096812 0.053639847
## 175 0.014757969 0.014757969 0.954022989
## 176 0.632113341 0.632113341 0.160919540
## 177 0.170011806 0.170011806 0.659003831
## 178 0.689885872 0.689885872 0.111111111
## 179 0.400236128 0.400236128 0.340996169
## 180 0.077922078 0.077922078 0.850574713
## 181 0.405903188 0.405903188 0.337164751
## 182 0.123730815 0.123730815 0.739463602
## 183 0.367768595 0.367768595 0.390804598
## 184 0.030696576 0.030696576 0.923371648
## 185 0.564738292 0.564738292 0.210727969
## 186 0.324970484 0.324970484 0.455938697
## 187 0.034238489 0.034238489 0.915708812
## 188 0.328807556 0.328807556 0.444444444
## 189 0.152499016 0.152499016 0.685823755
## 190 0.226682409 0.226682409 0.586206897
## 191 0.690672963 0.690672963 0.107279693
## 192 0.118654073 0.118654073 0.754789272
## 193 0.736586646 0.736586646 0.076628352
## 194 0.043093270 0.043093270 0.892720307
## 195 0.777646596 0.777646596 0.065134100
## 196 0.467532468 0.467532468 0.283524904
## 197 0.621802440 0.621802440 0.172413793
## 198 0.198937426 0.198937426 0.620689655
## 199 0.552538371 0.552538371 0.222222222
## 200 0.133116883 0.133116883 0.720306513
## 201 0.852420307 0.852420307 0.022988506
## 202 0.113341204 0.113341204 0.762452107
## 203 0.149547422 0.149547422 0.689655172
## 204 0.220779221 0.220779221 0.590038314
## 205 0.912632822 0.912632822 0.019157088
## 206 0.312278630 0.312278630 0.478927203
## 207 0.040436836 0.040436836 0.904214559
## 208 0.161072694 0.161072694 0.666666667
## 209 0.415289256 0.415289256 0.329501916
## 210 0.377213695 0.377213695 0.375478927
## 211 0.009445100 0.009445100 0.977011494
## 212 0.416765053 0.416765053 0.325670498
## 213 0.591263282 0.591263282 0.187739464
## 214 0.628605161 0.628605161 0.164750958
## 215 0.313105077 0.313105077 0.475095785
## 216 0.467532468 0.467532468 0.287356322
## 217 0.029515939 0.029515939 0.931034483
## 218 0.096221960 0.096221960 0.793103448
## 219 0.339433294 0.339433294 0.425287356
## 220 0.097992916 0.097992916 0.785440613
## 221 0.736245573 0.736245573 0.080459770
## 222 0.030303030 0.030303030 0.927203065
## 223 0.102715466 0.102715466 0.777777778
## 224 0.384651712 0.384651712 0.363984674
## 225 0.360881543 0.360881543 0.398467433
## 226 0.632428178 0.632428178 0.157088123
## 227 0.814639906 0.814639906 0.042145594
## 228 0.121343303 0.121343303 0.750957854
## 229 0.158795750 0.158795750 0.674329502
## 230 0.407319953 0.407319953 0.333333333
## 231 0.001180638 0.001180638 0.988505747
## 232 0.154663518 0.154663518 0.678160920
## 233 0.702951594 0.702951594 0.103448276
## 234 0.373081464 0.373081464 0.386973180
## 235 0.520923521 0.520923521 0.252873563
## 236 0.265938607 0.265938607 0.521072797
## 237 0.229634002 0.229634002 0.578544061
## 238 0.165092483 0.165092483 0.662835249
## 239 0.204840614 0.204840614 0.609195402
## 240 0.429752066 0.429752066 0.306513410
## 241 0.095238095 0.095238095 0.800766284
## 242 0.010625738 0.010625738 0.969348659
## 243 0.433293979 0.433293979 0.302681992
## 244 0.423258560 0.423258560 0.318007663
## 245 0.421015348 0.421015348 0.321839080
## 246 0.336650363 0.336650363 0.432950192
## 247 0.680243998 0.680243998 0.122605364
## 248 0.938842975 0.938842975 0.007662835
## 249 0.252951594 0.252951594 0.547892720
## 250 0.121605667 0.121605667 0.747126437
## 251 0.262691854 0.262691854 0.536398467
## 252 0.096221960 0.096221960 0.796934866
## 253 0.793388430 0.793388430 0.057471264
## 254 0.154663518 0.154663518 0.681992337
## 255 0.335694608 0.335694608 0.436781609
## 256 0.027154664 0.027154664 0.938697318
## 257 0.270365998 0.270365998 0.517241379
## 258 0.932703660 0.932703660 0.011494253
## 259 0.082644628 0.082644628 0.831417625
## 260 0.090200708 0.090200708 0.812260536
## 261 0.768763704 0.768763704 0.068965517
## 262 0.399449036 0.399449036 0.344827586library(class)
dat_pred <- knn(dat_train, dat_test, dataTestBowling[1:183, 2], k = 3)
table(dat_pred, dat[184:262, 2])##
## dat_pred 9 16 17 31 33 33.6666666666667 34 37 42.25 44.5 78 84.4
## 8 1 0 0 0 0 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0 0 0 0 0 0
## 16.3333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 17 0 1 1 0 0 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0 0 0 0 0 0
## 25.5 0 0 0 1 0 0 0 0 0 0 0 0
## 32 0 0 0 0 1 0 0 0 0 0 0 0
## 34 0 0 0 0 0 0 0 0 0 0 0 0
## 38 0 0 0 0 0 1 1 0 0 0 0 0
## 38.4285714285714 0 0 0 0 0 0 0 1 0 0 0 0
## 43.2857142857143 0 0 0 0 0 0 0 0 0 0 0 0
## 43.4 0 0 0 0 0 0 0 0 1 1 0 0
## 44.6666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 45 0 0 0 0 0 0 0 0 0 0 0 0
## 47 0 0 0 0 0 0 0 0 0 0 0 0
## 55 0 0 0 0 0 0 0 0 0 0 0 0
## 57.5 0 0 0 0 0 0 0 0 0 0 0 0
## 58 0 0 0 0 0 0 0 0 0 0 0 0
## 60.6666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 65 0 0 0 0 0 0 0 0 0 0 0 0
## 73 0 0 0 0 0 0 0 0 0 0 0 0
## 74 0 0 0 0 0 0 0 0 0 0 0 0
## 75.5 0 0 0 0 0 0 0 0 0 0 0 0
## 76.25 0 0 0 0 0 0 0 0 0 0 0 0
## 77 0 0 0 0 0 0 0 0 0 0 1 0
## 78.2 0 0 0 0 0 0 0 0 0 0 0 0
## 80 0 0 0 0 0 0 0 0 0 0 0 0
## 81 0 0 0 0 0 0 0 0 0 0 0 0
## 81.5 0 0 0 0 0 0 0 0 0 0 0 1
## 87 0 0 0 0 0 0 0 0 0 0 0 0
## 88 0 0 0 0 0 0 0 0 0 0 0 0
## 90 0 0 0 0 0 0 0 0 0 0 0 0
## 91 0 0 0 0 0 0 0 0 0 0 0 0
## 98 0 0 0 0 0 0 0 0 0 0 0 0
## 102.5 0 0 0 0 0 0 0 0 0 0 0 0
## 107 0 0 0 0 0 0 0 0 0 0 0 0
## 111 0 0 0 0 0 0 0 0 0 0 0 0
## 112.8 0 0 0 0 0 0 0 0 0 0 0 0
## 115.5 0 0 0 0 0 0 0 0 0 0 0 0
## 117.1 0 0 0 0 0 0 0 0 0 0 0 0
## 117.166666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 118 0 0 0 0 0 0 0 0 0 0 0 0
## 121 0 0 0 0 0 0 0 0 0 0 0 0
## 123.555555555556 0 0 0 0 0 0 0 0 0 0 0 0
## 128 0 0 0 0 0 0 0 0 0 0 0 0
## 128.571428571429 0 0 0 0 0 0 0 0 0 0 0 0
## 128.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 129 0 0 0 0 0 0 0 0 0 0 0 0
## 132.25 0 0 0 0 0 0 0 0 0 0 0 0
## 144 0 0 0 0 0 0 0 0 0 0 0 0
## 152 0 0 0 0 0 0 0 0 0 0 0 0
## 152.25 0 0 0 0 0 0 0 0 0 0 0 0
## 153.285714285714 0 0 0 0 0 0 0 0 0 0 0 0
## 154 0 0 0 0 0 0 0 0 0 0 0 0
## 155 0 0 0 0 0 0 0 0 0 0 0 0
## 157.6 0 0 0 0 0 0 0 0 0 0 0 0
## 158.25 0 0 0 0 0 0 0 0 0 0 0 0
## 163 0 0 0 0 0 0 0 0 0 0 0 0
## 168.5 0 0 0 0 0 0 0 0 0 0 0 0
## 171 0 0 0 0 0 0 0 0 0 0 0 0
## 180 0 0 0 0 0 0 0 0 0 0 0 0
## 180.5 0 0 0 0 0 0 0 0 0 0 0 0
## 183.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 187 0 0 0 0 0 0 0 0 0 0 0 0
## 188 0 0 0 0 0 0 0 0 0 0 0 0
## 200.25 0 0 0 0 0 0 0 0 0 0 0 0
## 204.8 0 0 0 0 0 0 0 0 0 0 0 0
## 206.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 212 0 0 0 0 0 0 0 0 0 0 0 0
## 213.875 0 0 0 0 0 0 0 0 0 0 0 0
## 215.714285714286 0 0 0 0 0 0 0 0 0 0 0 0
## 220.5 0 0 0 0 0 0 0 0 0 0 0 0
## 221.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 223 0 0 0 0 0 0 0 0 0 0 0 0
## 231 0 0 0 0 0 0 0 0 0 0 0 0
## 232.111111111111 0 0 0 0 0 0 0 0 0 0 0 0
## 238 0 0 0 0 0 0 0 0 0 0 0 0
## 241 0 0 0 0 0 0 0 0 0 0 0 0
## 251.75 0 0 0 0 0 0 0 0 0 0 0 0
## 253.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 254.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 263 0 0 0 0 0 0 0 0 0 0 0 0
## 264.833333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 266 0 0 0 0 0 0 0 0 0 0 0 0
## 273.833333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 274 0 0 0 0 0 0 0 0 0 0 0 0
## 274.5 0 0 0 0 0 0 0 0 0 0 0 0
## 281.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 283.875 0 0 0 0 0 0 0 0 0 0 0 0
## 285.75 0 0 0 0 0 0 0 0 0 0 0 0
## 291.2 0 0 0 0 0 0 0 0 0 0 0 0
## 294.5 0 0 0 0 0 0 0 0 0 0 0 0
## 295.5 0 0 0 0 0 0 0 0 0 0 0 0
## 298 0 0 0 0 0 0 0 0 0 0 0 0
## 300.5 0 0 0 0 0 0 0 0 0 0 0 0
## 311.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 313 0 0 0 0 0 0 0 0 0 0 0 0
## 316 0 0 0 0 0 0 0 0 0 0 0 0
## 319.5 0 0 0 0 0 0 0 0 0 0 0 0
## 325.5 0 0 0 0 0 0 0 0 0 0 0 0
## 327 0 0 0 0 0 0 0 0 0 0 0 0
## 329 0 0 0 0 0 0 0 0 0 0 0 0
## 332 0 0 0 0 0 0 0 0 0 0 0 0
## 337.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 341 0 0 0 0 0 0 0 0 0 0 0 0
## 344 0 0 0 0 0 0 0 0 0 0 0 0
## 345 0 0 0 0 0 0 0 0 0 0 0 0
## 347 0 0 0 0 0 0 0 0 0 0 0 0
## 351.8 0 0 0 0 0 0 0 0 0 0 0 0
## 366.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 367 0 0 0 0 0 0 0 0 0 0 0 0
## 377.428571428571 0 0 0 0 0 0 0 0 0 0 0 0
## 381 0 0 0 0 0 0 0 0 0 0 0 0
## 381.5 0 0 0 0 0 0 0 0 0 0 0 0
## 408.833333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 421.2 0 0 0 0 0 0 0 0 0 0 0 0
## 422.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 426.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 429.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 434.2 0 0 0 0 0 0 0 0 0 0 0 0
## 438.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 454 0 0 0 0 0 0 0 0 0 0 0 0
## 460.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 463 0 0 0 0 0 0 0 0 0 0 0 0
## 468.714285714286 0 0 0 0 0 0 0 0 0 0 0 0
## 469 0 0 0 0 0 0 0 0 0 0 0 0
## 469.166666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 472.25 0 0 0 0 0 0 0 0 0 0 0 0
## 480.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 482.75 0 0 0 0 0 0 0 0 0 0 0 0
## 488 0 0 0 0 0 0 0 0 0 0 0 0
## 496.75 0 0 0 0 0 0 0 0 0 0 0 0
## 502.25 0 0 0 0 0 0 0 0 0 0 0 0
## 503.6 0 0 0 0 0 0 0 0 0 0 0 0
## 508 0 0 0 0 0 0 0 0 0 0 0 0
## 510.833333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 518.6 0 0 0 0 0 0 0 0 0 0 0 0
## 527 0 0 0 0 0 0 0 0 0 0 0 0
## 538 0 0 0 0 0 0 0 0 0 0 0 0
## 543.4 0 0 0 0 0 0 0 0 0 0 0 0
## 545.142857142857 0 0 0 0 0 0 0 0 0 0 0 0
## 562.2 0 0 0 0 0 0 0 0 0 0 0 0
## 569 0 0 0 0 0 0 0 0 0 0 0 0
## 570.9 0 0 0 0 0 0 0 0 0 0 0 0
## 576.5 0 0 0 0 0 0 0 0 0 0 0 0
## 580.6 0 0 0 0 0 0 0 0 0 0 0 0
## 581.875 0 0 0 0 0 0 0 0 0 0 0 0
## 583.9 0 0 0 0 0 0 0 0 0 0 0 0
## 588.142857142857 0 0 0 0 0 0 0 0 0 0 0 0
## 591.166666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 592.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 616 0 0 0 0 0 0 0 0 0 0 0 0
## 617.25 0 0 0 0 0 0 0 0 0 0 0 0
## 618 0 0 0 0 0 0 0 0 0 0 0 0
## 623.5 0 0 0 0 0 0 0 0 0 0 0 0
## 626.666666666667 0 0 0 0 0 0 0 0 0 0 0 0
## 645.5 0 0 0 0 0 0 0 0 0 0 0 0
## 673.25 0 0 0 0 0 0 0 0 0 0 0 0
## 680.6 0 0 0 0 0 0 0 0 0 0 0 0
## 688.25 0 0 0 0 0 0 0 0 0 0 0 0
## 697.8 0 0 0 0 0 0 0 0 0 0 0 0
## 719 0 0 0 0 0 0 0 0 0 0 0 0
## 721 0 0 0 0 0 0 0 0 0 0 0 0
## 727.4 0 0 0 0 0 0 0 0 0 0 0 0
## 791.333333333333 0 0 0 0 0 0 0 0 0 0 0 0
## 840.5 0 0 0 0 0 0 0 0 0 0 0 0
## 855 0 0 0 0 0 0 0 0 0 0 0 0
##
## dat_pred 88.6666666666667 89.5 91 95 104 108.5 110.777777777778
## 8 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0
## 16.3333333333333 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0
## 34 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0
## 38.4285714285714 0 0 0 0 0 0 0
## 43.2857142857143 0 0 0 0 0 0 0
## 43.4 0 0 0 0 0 0 0
## 44.6666666666667 0 0 0 0 0 0 0
## 45 0 0 0 0 0 0 0
## 47 0 0 0 0 0 0 0
## 55 0 0 0 0 0 0 0
## 57.5 0 0 0 0 0 0 0
## 58 0 0 0 0 0 0 0
## 60.6666666666667 0 0 0 0 0 0 0
## 65 0 0 0 0 0 0 0
## 73 0 0 0 0 0 0 0
## 74 0 0 0 0 0 0 0
## 75.5 0 0 0 0 0 0 0
## 76.25 0 0 0 0 0 0 0
## 77 0 0 0 0 0 0 0
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##
## dat_pred 111 120.75 134.666666666667 137.166666666667 139 142.5
## 8 0 0 0 0 0 0
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##
## dat_pred 144.428571428571 147.833333333333 176.5 181.5 195 200
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##
## dat_pred 202.5 222.25 230.5 233.25 237 272.5 273.2 283.25 286.5
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##
## dat_pred 313.666666666667 324 327.5 333.8 346.333333333333 353
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##
## dat_pred 359.75 361 364.6 366.5 372 375 404 449.222222222222 476
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##
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## 840.5 0 0 0
## 855 0 0 0
##
## dat_pred 540.428571428571 543.666666666667 584.166666666667 593
## 8 0 0 0 0
## 11 0 0 0 0
## 13 0 0 0 0
## 16.3333333333333 0 0 0 0
## 17 0 0 0 0
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## 20.5 0 0 0 0
## 23 0 0 0 0
## 24 0 0 0 0
## 25.5 0 0 0 0
## 32 0 0 0 0
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## 38.4285714285714 0 0 0 0
## 43.2857142857143 0 0 0 0
## 43.4 0 0 0 0
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## 47 0 0 0 0
## 55 0 0 0 0
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## 58 0 0 0 0
## 60.6666666666667 0 0 0 0
## 65 0 0 0 0
## 73 0 0 0 0
## 74 0 0 0 0
## 75.5 0 0 0 0
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## 81 0 0 0 0
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## 88 0 0 0 0
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## 91 0 0 0 0
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## 111 0 0 0 0
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## 251.75 0 0 0 0
## 253.333333333333 0 0 0 0
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## 263 0 0 0 0
## 264.833333333333 0 0 0 0
## 266 0 0 0 0
## 273.833333333333 0 0 0 0
## 274 0 0 0 0
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## 281.333333333333 0 0 0 0
## 283.875 0 0 0 0
## 285.75 0 0 0 0
## 291.2 0 0 0 0
## 294.5 0 0 0 0
## 295.5 0 0 0 0
## 298 0 0 0 0
## 300.5 0 0 0 0
## 311.333333333333 0 0 0 0
## 313 0 0 0 0
## 316 0 0 0 0
## 319.5 0 0 0 0
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## 367 0 0 0 0
## 377.428571428571 0 0 0 0
## 381 0 0 0 0
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## 421.2 0 0 0 0
## 422.666666666667 0 0 0 0
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## 429.333333333333 0 0 0 0
## 434.2 0 0 0 0
## 438.333333333333 0 0 0 0
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## 463 0 0 0 0
## 468.714285714286 0 0 0 0
## 469 0 0 0 0
## 469.166666666667 0 0 0 0
## 472.25 0 0 0 0
## 480.333333333333 0 0 0 0
## 482.75 0 0 0 0
## 488 0 0 0 0
## 496.75 0 0 0 0
## 502.25 0 0 0 0
## 503.6 0 0 0 0
## 508 0 0 0 0
## 510.833333333333 0 0 0 0
## 518.6 0 0 0 0
## 527 0 0 0 0
## 538 0 1 0 0
## 543.4 1 0 0 0
## 545.142857142857 0 0 0 0
## 562.2 0 0 0 0
## 569 0 0 0 0
## 570.9 0 0 0 0
## 576.5 0 0 0 0
## 580.6 0 0 0 0
## 581.875 0 0 0 0
## 583.9 0 0 1 0
## 588.142857142857 0 0 0 0
## 591.166666666667 0 0 0 1
## 592.333333333333 0 0 0 0
## 616 0 0 0 0
## 617.25 0 0 0 0
## 618 0 0 0 0
## 623.5 0 0 0 0
## 626.666666666667 0 0 0 0
## 645.5 0 0 0 0
## 673.25 0 0 0 0
## 680.6 0 0 0 0
## 688.25 0 0 0 0
## 697.8 0 0 0 0
## 719 0 0 0 0
## 721 0 0 0 0
## 727.4 0 0 0 0
## 791.333333333333 0 0 0 0
## 840.5 0 0 0 0
## 855 0 0 0 0
##
## dat_pred 603.4 631.6 631.888888888889 659.142857142857
## 8 0 0 0 0
## 11 0 0 0 0
## 13 0 0 0 0
## 16.3333333333333 0 0 0 0
## 17 0 0 0 0
## 18 0 0 0 0
## 20.5 0 0 0 0
## 23 0 0 0 0
## 24 0 0 0 0
## 25.5 0 0 0 0
## 32 0 0 0 0
## 34 0 0 0 0
## 38 0 0 0 0
## 38.4285714285714 0 0 0 0
## 43.2857142857143 0 0 0 0
## 43.4 0 0 0 0
## 44.6666666666667 0 0 0 0
## 45 0 0 0 0
## 47 0 0 0 0
## 55 0 0 0 0
## 57.5 0 0 0 0
## 58 0 0 0 0
## 60.6666666666667 0 0 0 0
## 65 0 0 0 0
## 73 0 0 0 0
## 74 0 0 0 0
## 75.5 0 0 0 0
## 76.25 0 0 0 0
## 77 0 0 0 0
## 78.2 0 0 0 0
## 80 0 0 0 0
## 81 0 0 0 0
## 81.5 0 0 0 0
## 87 0 0 0 0
## 88 0 0 0 0
## 90 0 0 0 0
## 91 0 0 0 0
## 98 0 0 0 0
## 102.5 0 0 0 0
## 107 0 0 0 0
## 111 0 0 0 0
## 112.8 0 0 0 0
## 115.5 0 0 0 0
## 117.1 0 0 0 0
## 117.166666666667 0 0 0 0
## 118 0 0 0 0
## 121 0 0 0 0
## 123.555555555556 0 0 0 0
## 128 0 0 0 0
## 128.571428571429 0 0 0 0
## 128.666666666667 0 0 0 0
## 129 0 0 0 0
## 132.25 0 0 0 0
## 144 0 0 0 0
## 152 0 0 0 0
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## 154 0 0 0 0
## 155 0 0 0 0
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## 158.25 0 0 0 0
## 163 0 0 0 0
## 168.5 0 0 0 0
## 171 0 0 0 0
## 180 0 0 0 0
## 180.5 0 0 0 0
## 183.333333333333 0 0 0 0
## 187 0 0 0 0
## 188 0 0 0 0
## 200.25 0 0 0 0
## 204.8 0 0 0 0
## 206.333333333333 0 0 0 0
## 212 0 0 0 0
## 213.875 0 0 0 0
## 215.714285714286 0 0 0 0
## 220.5 0 0 0 0
## 221.666666666667 0 0 0 0
## 223 0 0 0 0
## 231 0 0 0 0
## 232.111111111111 0 0 0 0
## 238 0 0 0 0
## 241 0 0 0 0
## 251.75 0 0 0 0
## 253.333333333333 0 0 0 0
## 254.666666666667 0 0 0 0
## 263 0 0 0 0
## 264.833333333333 0 0 0 0
## 266 0 0 0 0
## 273.833333333333 0 0 0 0
## 274 0 0 0 0
## 274.5 0 0 0 0
## 281.333333333333 0 0 0 0
## 283.875 0 0 0 0
## 285.75 0 0 0 0
## 291.2 0 0 0 0
## 294.5 0 0 0 0
## 295.5 0 0 0 0
## 298 0 0 0 0
## 300.5 0 0 0 0
## 311.333333333333 0 0 0 0
## 313 0 0 0 0
## 316 0 0 0 0
## 319.5 0 0 0 0
## 325.5 0 0 0 0
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## 332 0 0 0 0
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## 366.666666666667 0 0 0 0
## 367 0 0 0 0
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## 381 0 0 0 0
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## 421.2 0 0 0 0
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## 434.2 0 0 0 0
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## 454 0 0 0 0
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## 463 0 0 0 0
## 468.714285714286 0 0 0 0
## 469 0 0 0 0
## 469.166666666667 0 0 0 0
## 472.25 0 0 0 0
## 480.333333333333 0 0 0 0
## 482.75 0 0 0 0
## 488 0 0 0 0
## 496.75 0 0 0 0
## 502.25 0 0 0 0
## 503.6 0 0 0 0
## 508 0 0 0 0
## 510.833333333333 0 0 0 0
## 518.6 0 0 0 0
## 527 0 0 0 0
## 538 0 0 0 0
## 543.4 0 0 0 0
## 545.142857142857 0 0 0 0
## 562.2 0 0 0 0
## 569 0 0 0 0
## 570.9 0 0 0 0
## 576.5 0 0 0 0
## 580.6 0 0 0 0
## 581.875 0 0 0 0
## 583.9 0 0 0 0
## 588.142857142857 0 0 0 0
## 591.166666666667 0 0 0 0
## 592.333333333333 1 0 0 0
## 616 0 0 0 0
## 617.25 0 0 0 0
## 618 0 0 0 0
## 623.5 0 1 0 0
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## 645.5 0 0 1 1
## 673.25 0 0 0 0
## 680.6 0 0 0 0
## 688.25 0 0 0 0
## 697.8 0 0 0 0
## 719 0 0 0 0
## 721 0 0 0 0
## 727.4 0 0 0 0
## 791.333333333333 0 0 0 0
## 840.5 0 0 0 0
## 855 0 0 0 0
##
## dat_pred 666.666666666667 680 698 730 781 798 803.2
## 8 0 0 0 0 0 0 0
## 11 0 0 0 0 0 0 0
## 13 0 0 0 0 0 0 0
## 16.3333333333333 0 0 0 0 0 0 0
## 17 0 0 0 0 0 0 0
## 18 0 0 0 0 0 0 0
## 20.5 0 0 0 0 0 0 0
## 23 0 0 0 0 0 0 0
## 24 0 0 0 0 0 0 0
## 25.5 0 0 0 0 0 0 0
## 32 0 0 0 0 0 0 0
## 34 0 0 0 0 0 0 0
## 38 0 0 0 0 0 0 0
## 38.4285714285714 0 0 0 0 0 0 0
## 43.2857142857143 0 0 0 0 0 0 0
## 43.4 0 0 0 0 0 0 0
## 44.6666666666667 0 0 0 0 0 0 0
## 45 0 0 0 0 0 0 0
## 47 0 0 0 0 0 0 0
## 55 0 0 0 0 0 0 0
## 57.5 0 0 0 0 0 0 0
## 58 0 0 0 0 0 0 0
## 60.6666666666667 0 0 0 0 0 0 0
## 65 0 0 0 0 0 0 0
## 73 0 0 0 0 0 0 0
## 74 0 0 0 0 0 0 0
## 75.5 0 0 0 0 0 0 0
## 76.25 0 0 0 0 0 0 0
## 77 0 0 0 0 0 0 0
## 78.2 0 0 0 0 0 0 0
## 80 0 0 0 0 0 0 0
## 81 0 0 0 0 0 0 0
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## 128 0 0 0 0 0 0 0
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## 129 0 0 0 0 0 0 0
## 132.25 0 0 0 0 0 0 0
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## 154 0 0 0 0 0 0 0
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## 157.6 0 0 0 0 0 0 0
## 158.25 0 0 0 0 0 0 0
## 163 0 0 0 0 0 0 0
## 168.5 0 0 0 0 0 0 0
## 171 0 0 0 0 0 0 0
## 180 0 0 0 0 0 0 0
## 180.5 0 0 0 0 0 0 0
## 183.333333333333 0 0 0 0 0 0 0
## 187 0 0 0 0 0 0 0
## 188 0 0 0 0 0 0 0
## 200.25 0 0 0 0 0 0 0
## 204.8 0 0 0 0 0 0 0
## 206.333333333333 0 0 0 0 0 0 0
## 212 0 0 0 0 0 0 0
## 213.875 0 0 0 0 0 0 0
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## 283.875 0 0 0 0 0 0 0
## 285.75 0 0 0 0 0 0 0
## 291.2 0 0 0 0 0 0 0
## 294.5 0 0 0 0 0 0 0
## 295.5 0 0 0 0 0 0 0
## 298 0 0 0 0 0 0 0
## 300.5 0 0 0 0 0 0 0
## 311.333333333333 0 0 0 0 0 0 0
## 313 0 0 0 0 0 0 0
## 316 0 0 0 0 0 0 0
## 319.5 0 0 0 0 0 0 0
## 325.5 0 0 0 0 0 0 0
## 327 0 0 0 0 0 0 0
## 329 0 0 0 0 0 0 0
## 332 0 0 0 0 0 0 0
## 337.333333333333 0 0 0 0 0 0 0
## 341 0 0 0 0 0 0 0
## 344 0 0 0 0 0 0 0
## 345 0 0 0 0 0 0 0
## 347 0 0 0 0 0 0 0
## 351.8 0 0 0 0 0 0 0
## 366.666666666667 0 0 0 0 0 0 0
## 367 0 0 0 0 0 0 0
## 377.428571428571 0 0 0 0 0 0 0
## 381 0 0 0 0 0 0 0
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## 408.833333333333 0 0 0 0 0 0 0
## 421.2 0 0 0 0 0 0 0
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## 426.333333333333 0 0 0 0 0 0 0
## 429.333333333333 0 0 0 0 0 0 0
## 434.2 0 0 0 0 0 0 0
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## 454 0 0 0 0 0 0 0
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## 472.25 0 0 0 0 0 0 0
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## 482.75 0 0 0 0 0 0 0
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## 508 0 0 0 0 0 0 0
## 510.833333333333 0 0 0 0 0 0 0
## 518.6 0 0 0 0 0 0 0
## 527 0 0 0 0 0 0 0
## 538 0 0 0 0 0 0 0
## 543.4 0 0 0 0 0 0 0
## 545.142857142857 0 0 0 0 0 0 0
## 562.2 0 0 0 0 0 0 0
## 569 0 0 0 0 0 0 0
## 570.9 0 0 0 0 0 0 0
## 576.5 0 0 0 0 0 0 0
## 580.6 0 0 0 0 0 0 0
## 581.875 0 0 0 0 0 0 0
## 583.9 0 0 0 0 0 0 0
## 588.142857142857 0 0 0 0 0 0 0
## 591.166666666667 0 0 0 0 0 0 0
## 592.333333333333 0 0 0 0 0 0 0
## 616 0 0 0 0 0 0 0
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## 623.5 0 0 0 0 0 0 0
## 626.666666666667 0 0 0 0 0 0 0
## 645.5 1 0 0 0 0 0 0
## 673.25 0 1 0 0 0 0 0
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## 697.8 0 0 1 0 0 0 0
## 719 0 0 0 1 0 0 0
## 721 0 0 0 0 0 0 0
## 727.4 0 0 0 0 0 0 0
## 791.333333333333 0 0 0 0 1 0 1
## 840.5 0 0 0 0 0 1 0
## 855 0 0 0 0 0 0 0plot(dat_pred)